diff Code/Classifiers/SVM_Singing.m @ 4:92ca03a8fa99 tip

Update to ICASSP 2013 benchmark

--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/Code/Classifiers/SVM_Singing.m	Wed Feb 13 11:02:39 2013 +0000
@@ -0,0 +1,242 @@
+function [] = SVM_Singing( inputFileName )
+
+cd 'C:\Users\dawn\Dropbox\TestResults'
+
+DEBUG = 1;
+% output results file name
+% masterFileOutputID = fopen( 'SVM_Singing_HNR.txt', 'a' );
+outputFileName = ['SVM_' inputFileName];
+masterFileOutputID = fopen( outputFileName, 'a' );
+
+% input results file name
+% inputFileName = 'singingBasicHNRStats.txt';
+
+fprintf( masterFileOutputID, '\n RESULTS FILE NAME: %s\n', inputFileName);
+inputFileID = fopen( inputFileName );
+
+% noOfArguments = length(varargin);
+
+% outputFileName = 'individualResults/SVM_Results_';
+% resultsFileName = 'SVM_Results_';
+titleName = '';
+% for i=1 : noOfArguments
+%     titleName = [ titleName varargin{i} '_'];
+%     fprintf( masterFileOutputID, '%s_', varargin{i} );
+% end
+
+% outputFileName = [ outputFileName titleName ];
+% resultsFileName = [ resultsFileName titleName ];
+
+fprintf( masterFileOutputID, '\t' );
+
+% outputFileName = [ outputFileName '.txt'];
+% resultsFileName = [ resultsFileName '.txt'];
+% 
+% fileOutputID = fopen( outputFileName, 'w' );
+% fileSVMOutputID = fopen( resultsFileName, 'w' );
+
+% -------------------- get the data from the results file ---------------
+lineCount = 0;
+fileCount = 0;
+data = [];
+groups = [];
+
+while( ~(feof(inputFileID)) )
+    
+    outputValues = [];
+    thestr = fgetl(inputFileID);
+    fileCount = fileCount + 1;
+
+    % determine whether we have a positive or negative sample
+    sampleEmotion( fileCount ) = 'U';
+    if( ~(isempty(strfind(thestr,'pos'))))
+        % sample is positive
+        sampleEmotion( fileCount ) = 'P';
+        groups( fileCount ) = 1;
+    elseif( ~(isempty(strfind(thestr,'neg'))))
+        % sample is negative
+        sampleEmotion( fileCount ) = 'N';
+        groups( fileCount ) = 0;
+    else
+        disp('EEEK!');
+        fileCount = fileCount - 1;
+%         pause;
+    end
+
+    % determine whether we have a male, female or trans sample
+%     gender( fileCount ) = '?';
+%     if( ~(isempty(strfind(thestr,'fem'))))
+%         % gender is female
+%         gender( fileCount ) = 'F';
+%     elseif( ~(isempty(strfind(thestr,'male'))))
+%         % gender is male
+%         gender( fileCount ) = 'M';
+%     elseif( ~(isempty(strfind(thestr,'trans'))))
+%         % gender is trans
+%         gender( fileCount ) = 'T';
+%     else
+%         disp('EEEK!');
+%         pause;
+%     end
+
+    if(( ~(isempty(strfind(thestr,'pos')))) || ( ~(isempty(strfind(thestr,'neg')))) )
+        %how many values are in the string?
+%         spaces = strfind( thestr, ' ' );
+        spaces = [ strfind( thestr,  sprintf('\t')) strfind( thestr, ' ' )];
+        numberstr = thestr( spaces(1) : end ); % chop off the file name  
+        vars = sscanf( numberstr, '%f', inf );
+        data( fileCount, : ) = vars;
+    end
+        
+    lineCount = lineCount + 1;
+    
+end
+fclose(inputFileID);
+
+% ------------  apply the SVM classifier  ------------------------
+
+resultMatrix = [];
+
+noOfIterations = 100;
+
+for n = 1:noOfIterations
+    % Randomly select training and test sets, perhaps we should try all and
+    % choose the best?
+    [train, test] = crossvalind('holdOut',groups);
+    cp = classperf(groups);
+    
+    % Use a linear support vector machine classifier
+    svmStruct = svmtrain(data(train,:),groups(train));
+    classes = svmclassify(svmStruct,data(test,:));
+    % See how well the classifier performed
+    classperf(cp,classes,test);
+    numbers = cp.CountingMatrix;
+
+    resultMatrix (n,:,:) = cp.DiagnosticTable;
+%     
+end
+
+
+
+
+% for emotion detection give the confusion matrix as 
+    % -----------------------------------------------------------------
+    % positive correctly identified         | positive incorrectly identified (1,2)
+    % negative incorrectly identified (2,1) | negative correctly identified
+    % ------------------------------------------------------------------
+    
+% takes the average of 100 iterations - do we want to take the best?  
+
+meanResults(1,1) = mean( resultMatrix(:,1,1) );
+meanResults(1,2) = mean( resultMatrix(:,2,1) );
+meanResults(2,1) = mean( resultMatrix(:,1,2) );
+meanResults(2,2) = mean( resultMatrix(:,2,2) );
+
+meanResults(3,:)=0;
+meanResults(:,3)=0;
+
+meanResults(3,3) = (meanResults(1,1) + meanResults(2,2));% / sum(sum(meanResults));
+
+% convert to percentages
+% how many of each sample do we have?
+groupNumbers = unique( groups( test ));
+groupNames = unique( sampleEmotion( test ));
+sampleEmotionTest = sampleEmotion( test );
+% which group is which emotion?
+thisGroupNumber = groupNumbers(1);
+thisGroup = find( groups( test ) == thisGroupNumber );
+thisGroupName = unique( sampleEmotionTest( thisGroup ));
+
+thatGroupNumber = groupNumbers(2);
+thatGroup = find( groups( test ) == thatGroupNumber );
+thatGroupName = unique( sampleEmotionTest( thatGroup ));
+
+if(length( thisGroupName ) ~= 1 )
+    disp('ARGH!');
+    pause;
+end
+
+thisGroupNumberOfSamples = length( thisGroup );
+thatGroupNumberOfSamples = length( thatGroup );
+
+if( thisGroupName == 'P' )
+    %swap all the variables ready for checking
+    temp = thisGroupNumberOfSamples;
+    thisGroupNumberOfSamples = thatGroupNumberOfSamples;
+    thatGroupNumberOfSamples = temp;
+    
+    temp = thisGroupName;
+    thisGroupName = thatGroupName
+    thatGroupName = temp;
+    disp('CHECK ME!');
+end
+
+if( thisGroupName == 'N' )
+     % group 0 is negative
+    if( sum( meanResults(1,:) ) == thisGroupNumberOfSamples )
+        %if the elements in the first row add up to the number of negative
+        %samples, then swap the rows because we want the top row to be the
+        %results for the positive samples
+        temp(:,1) = meanResults(1:2,2);
+        temp(:,2) = meanResults(1:2,1);
+        temp2(1,:) = temp(2,:);
+        temp2(2,:) = temp(1,:);
+        
+        meanResults(1:2,1) = temp2(:,1);
+        meanResults(1:2,2) = temp2(:,2);
+
+        % check the number of positive samples
+        if(( sum( meanResults(1,:) ) == thatGroupNumberOfSamples ) ...
+            && ( thatGroupName == 'P' ) )
+            % row 1 is positive
+            disp('matrix correct');
+        else
+            disp('ARGH!');
+            pause;
+        end
+
+    elseif( sum( meanResults(2,:) ) == thisGroupNumberOfSamples  )
+
+        % the elements in the second row add up to the number of negative
+        % samples, so the matrix is the correct way around
+
+        % check the number of positive samples
+        if(( sum( meanResults(1,:) ) == thatGroupNumberOfSamples ) ...
+            && ( thatGroupName == 'P' ) )
+            % row 0 is positive
+            disp('matrix correct');
+        else
+            disp('ARGH!');
+            pause;
+        end
+    end
+end
+
+% calculate the percentages
+numberOfSamples = sum(sum( meanResults(1:2,1:2)));
+percentageResults = meanResults;
+percentageResults(1,1) = meanResults(1,1) / numberOfSamples;
+percentageResults(1,2) = meanResults(1,2) / numberOfSamples;
+percentageResults(2,1) = meanResults(2,1) / numberOfSamples;
+percentageResults(2,2) = meanResults(2,2) / numberOfSamples;
+percentageResults(3,3) = meanResults(3,3) / numberOfSamples;
+
+percentageResults = percentageResults * 100
+
+confusionMatrix = percentageResults;
+ fprintf( masterFileOutputID, '\n %f \t %f \n %f \t %f \n %f \t %f \t %f \n', confusionMatrix(1,1), confusionMatrix(1,2), confusionMatrix(2,1), confusionMatrix(2,2), 0, 0, confusionMatrix(3,3));
+
+ % print latex results to the screen
+str1 = sprintf(' & %2.2f & %2.2f &  \\\\', percentageResults(1,1), percentageResults(1,2) );
+disp(str1);
+str1 = sprintf(' & %2.2f & %2.2f &  \\\\', percentageResults(2,1), percentageResults(2,2) );
+disp(str1);
+str1 = sprintf(' & & & %2.2f \\\\',percentageResults(3,3) );
+disp(str1);
+ 
+fprintf( masterFileOutputID, '\n' );
+fclose( masterFileOutputID );
+
+end
+
+